Commercial enterprises need accountability for the significant financial resources they spend on advertising products and services. Industries such as television have seen an erosion of advertising resources spent relative to other media (e.g., the Internet), in large part because of the perception of a lack of return on investment (ROI) accountability. The marketplace requires a solution to a significant challenge in marketing: accurately measuring each of the media in which a product is advertised to determine each medium's relative contribution to ROI with respect to advertisement expense. Advertisers need to know not only which consumers potentially viewed their commercials, but also how many of the consumers exposed to the advertising actually made purchases or acted in response to the advertising content.
To measure advertising effectiveness in television media, for example, the viewing behavior of millions of households must be monitored and analyzed across an increasingly complex array of different television channels and program offerings. The problem has been exacerbated by the fragmentation of television programming options available to consumers through digital cable channels, video-on-demand (VOD), digital video recorder (DVR), interactive television (iTV), and other diverse programming options. This problem has caused many advertisers to question the adequacy of current media accountability methodologies.
It is important to find ways to measure television advertisement exposure that are cost effective for a relatively large sample size of consumer households. A large sample is needed because the number of channels has become so great that the ratings for the channels themselves and especially the breakdowns of the audiences of specific programs by demographic groups typically become unstable and unreliable with smaller sample sizes employed with prior analysis methods. This means that the sample size must be sufficiently large to facilitate dissection of the results by exposure to media and marketing communications. In order for statistically significant results to emerge from analysis for a typical brand, sample sizes in the hundreds of thousands of households may be deemed to be required. However, such sample sizes are typically not cost effective in systems that require installation of new data collection hardware in the home. For example, one important analysis negatively impacted by the unavailability of an appropriate sample size is a comparison of how the composition of marketing communications reaching consumers who switched to a subject product brand differs from the composition of marketing communications reaching other users within the product category who did not switch to the subject brand. Because of the importance of ROI, of making marketing investments more predictable, and of integrating marketing into a company's financial model, most companies have engaged in econometric modeling to try to solve this problem. Many agree that such modeling lacks granularity and has numerous validity gaps, leading to little or no impact on finding ways to understand and increase ROI.
In addition, privacy has become one of the most salient concerns of consumers and legislatures since the arrival of the Internet. There is a sensitivity to the potential for privacy to be compromised by modern technology, including marketing and advertising systems that acquire personally identifiable information about consumers. Accordingly, the ways in which advertising data and consumer information are collected, processed and analyzed must address the need for consumer privacy.
In view of the issues described above, more effective and efficient systems, processes, tools and strategies are needed to provide advertisers and other users with accurate measurements of the efficacy of their media advertising campaigns while promoting and protecting consumer privacy, and for purposes of media optimization, targeting and addressability.